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An effective recognition of moving target seismic anomaly for security region based on deep bidirectional LSTM combined CNN

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Abstract

Ground motion target recognition based on seismic signals is more convenient and efficient than traditional manual patrol identification. However, current high-precision identification methods are limited to single-target classification. In this paper, the embedded adaptive learning technology was utilized to solve the problem of timeliness for the real-time moving target monitoring. We propose a deep bidirectional long short-term memory (DBiLSTM) algorithm that is implemented based on extracting spatial properties. The sequence data is processed by using three models including the convolutional neural network (CNN) and CNN-LSTM and CNN-DBiLSTM respectively, the target labels are categorized in the last layer. Identification results on the JL dataset are indicated that the CNN-DBiLSTM model produces the best performance. The algorithm we proposed improves the identification accuracy by 3.26% compared with the benchmark CNN method and the total number of layers of the network is only five. And the stability is the best among the three algorithms in ten independent experiments. Which Provides a practical classification and identification method for real-time target monitoring system.

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Data availability

The datasets analyzed during the current study are not publicly available due to the restrictions apply to the availability of these data, which were used under license for the current study. Data are available from the corresponding author on reasonable request.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China under Grant 41804167 and in part by the National Key R&D Program of China under Grant 2018YFC0603204.

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Authors and Affiliations

  1. College of Instrumentation and Electrical Engineering, Jilin University, Changchun, 130000, China

    Tongyu Nie, Sirui Wang, Yuqi Wang, Xunqian Tong & Feng Sun

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  1. Tongyu Nie
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Correspondence to Xunqian Tong or Feng Sun.

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Nie, T., Wang, S., Wang, Y. et al. An effective recognition of moving target seismic anomaly for security region based on deep bidirectional LSTM combined CNN. Multimed Tools Appl (2023). https://doi.org/10.1007/s11042-023-14382-5

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